class_docstr: An abstract search strategy with customized methods on the python-side.
  This is the user facing class for function overloading inheritance.
  
  Note: @derived_object is required for proper usage of any inherited class.
docstr: Generate measure candidates from design spaces for measurement.
  
  Returns
  -------
  measure_candidates : Optional[List[IRModule]]
      The measure candidates generated, None if finished.
docstr_tok: ["Generate","measure","candidates","from","design","spaces","for","measurement",".","Returns","--","--","--","-","measure_candidates",":","Optional","[","List","[","IRModule","]","]","The","measure","candidates","generated",",","None","if","finished","."]
code: def generate_measure_candidates(
      self,
  ) -> Optional[List[MeasureCandidate]]:
      """Generate measure candidates from design spaces for measurement.
  
      Returns
      -------
      measure_candidates : Optional[List[IRModule]]
          The measure candidates generated, None if finished.
      """
      raise NotImplementedError
  
imports: from typing import TYPE_CHECKING, Callable, List, Optional, Union
  from typing_extensions import Literal
  from tvm._ffi import register_object
  from tvm.runtime import Object
  from tvm.tir.schedule import Schedule
  from ..None import _ffi_api
  from ..arg_info import ArgInfo
  from ..runner import RunnerResult
label_desc: Use image node_id 4 for calling the PySearchStrategy obj's underlying member method code with example usage: obj.generate_measure_candidates() without return types